The approaches described in this section are approaches that could be pursued, but not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section.
Determining distributions of yield of crops from agricultural fields is essential for planning and evaluating agricultural management strategies. However, raw data representing yield of crops and obtained from field equipment is known to suffer from contamination such as errors. Some of the errors may be due to errors or shortcomings of the mechanisms used in the field to collect data about the yield of crops. For example, some of the data collection sensors on pieces of harvesting or other agricultural equipment may be incorrectly calibrated, and thus introducing some bias in the measured yield. Other errors may be inherent to the harvesting environment and conditions, including operational delays in registering harvested crops, improperly calibrated harvesting equipment including a harvester bar, incorrectly registered speed readings with which a harvester harvests the crops, narrow finishes of the harvesting combine, and errors caused by the harvester's turns and harvesting overlaps.
Decontaminating this data representing yield of crops is usually carried out by persons who visually inspect the data. The persons may be experts trained in applying various filters and thresholds to determine whether the data representing the yields is decontaminated. Based on the visual inspection and analysis of relations between the collected data and the thresholds, the experts may try to determine sources that caused the contamination. Unfortunately, the methods of selecting the filters and thresholds are typically random and unstructured, and thus do not offer a coherent and robust approach for decontaminating the data. Furthermore, it is often difficult to assess the effectiveness of the filters and thresholds with respect to their applicability to data harvested from different fields, using different harvesting equipment, and harvested using different crop harvesting techniques.